jik876/hifi-gan
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
This project helps create high-quality, natural-sounding speech audio from existing audio recordings or speech features. It takes in either raw audio files or mel-spectrograms (a visual representation of sound frequencies) and generates clear, high-fidelity human-like speech. This is ideal for anyone working with synthetic voice generation, such as content creators, accessibility developers, or researchers in text-to-speech.
2,328 stars. No commits in the last 6 months.
Use this if you need to efficiently generate realistic and high-quality synthetic speech from audio data or mel-spectrograms for single or multiple speakers.
Not ideal if you're looking to generate speech directly from text input without any intermediate audio or spectrogram data.
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2,328
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552
Language
Python
License
MIT
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Last pushed
Jul 27, 2024
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